FORM 2
THE PATENTS ACT, 1970 (39 OF 1970) & THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)
“METHOD AND SYSTEM FOR PERFORMING DELTA-ANALYSIS BY A SIMPLE NETWORK MANAGEMENT PROTOCOL (SNMP) PARSER”
We, Jio Platforms Limited, an Indian National, of Office - 101, Saffron, Nr. Centre Point, Panchwati 5 Rasta, Ambawadi, Ahmedabad - 380006, Gujarat, India.
The following specification particularly describes the invention and the manner in which it is to be performed.

METHOD AND SYSTEM FOR PERFORMING DELTA-ANALYSIS BY A SIMPLE NETWORK MANAGEMENT PROTOCOL (SNMP) PARSER
FIELD OF THE DISCLOSURE
[0001] Embodiments of the present disclosure generally relate to a network performance management system. More particularly, embodiments of the present disclosure relate to a method and system for providing a simple network management protocol (SNMP) parser for performing delta calculations in a network performance management system.
BACKGROUND
[0002] The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
[0003] Wireless communication technology has rapidly evolved over the past few decades, with each generation bringing significant improvements and advancements. The first generation of wireless communication technology was based on analog technology and offered only voice services. However, with the advent of the second-generation (2G) technology, digital communication and data services became possible, and text messaging was introduced. The third-generation (3G) technology marked the introduction of high-speed internet access, mobile video calling, and location-based services. The fourth-generation (4G) technology revolutionized wireless communication with faster data speeds, better network

coverage, and improved security. Currently, the fifth-generation (5G) technology is being deployed, promising even faster data speeds, low latency, and the ability to connect multiple devices simultaneously. With each generation, wireless communication technology has become more advanced, sophisticated, and capable of delivering more services to its users.
[0004] Network performance management systems typically track network elements and data from multiple network monitoring tools, they combine and process such data to determine key performance indicators (KPI) of the network. Integrated performance management systems provide the means to visualize the network performance data so that network operators and other relevant stakeholders are able to identify the service quality of the overall network, and individual/ grouped network elements. By having an overall as well as detailed view of the network performance, the network operators can detect, diagnose, and remedy actual service issues, as well as predict potential service issues or failures in the network and take precautionary measures accordingly.
[0005] Network nodes, such as a base station, an access point (AP), etc. may collect
event statistics in the form of performance counters and send them to the integrated
performance management system for diagnostic purposes. These
performance counters may be logged and maintained by the management system in order to assess the performance of the network nodes. These performance counters may be huge in number and therefore require large amount of time and resources for processing the same. In the present solutions, for collecting and analysing the data from said various network nodes, the collected raw data encompasses the entire aggregated data up to a particular moment, which poses challenges when performing different types of computations and analysis, which otherwise can be performed on the incremental data only which can be saved in delta files. This will reduce the time for computations as well as will consume less resources.

[0006] Thus, there exists an imperative need in the art to provide a solution for providing parsers for performing delta calculations, that can overcome these and other limitations of the existing solutions, which the present disclosure aims to address.
OBJECTS OF THE INVENTION
[0007] Some of the objects of the present disclosure, which at least one embodiment disclosed herein satisfies are listed herein below.
[0008] It is an object of the present disclosure to provide a system and a method for performing delta analysis by a simple network management protocol (SNMP) parser.
[0009] It is another object of the present disclosure to provide a solution for performing delta calculations which enables users to perform targeted computations and analysis, focusing only on the relevant data for a specific time period.
[0010] It is another object of the present disclosure to provide a solution that facilitates more accurate evaluations and enables informed decision-making.
[0011] It is yet another object of the present disclosure to provide a solution that is less resource intensive.
[0012] It is yet another object of the present disclosure to provide a solution that reduces time involved in performing computation and analysis.
SUMMARY

[0013] This section is provided to introduce certain aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.
[0014] According to an aspect of the present disclosure, a method for performing delta analysis by a simple network management protocol (SNMP) parser unit. The method comprises receiving, by a transceiver unit at the SNMP parser unit, a compressed raw data from a file system component at a pre-defined interval of time, wherein the raw data comprises one or more performance counters; determining, by an extraction unit at the SNMP parser unit, one of: an available status and an absent status of a previous file related to the compressed raw data, determining, by an analysis unit at the SNMP parser unit, for each performance counter of the one or more performance counters, an existence status of each performance counter in an omit list in an event of determination of the available status, wherein the existence status is one of: an existing status and a non-existing status, and wherein the existing status is determined in an event the performance counter is existing in the omit list, and the non-existing status is determined in an event the performance counter is not existing in the omit list; performing, by the analysis unit at the SNMP parser unit, a delta analysis for a subset of the one or more performance counters, wherein the subset of the one or more performance counters comprises a set of performance counters for which the non-existing status is determined; parsing, by a parser at the SNMP parser unit, a raw data file based on the performance of the delta analysis, to generate a parsed data file; storing, in a storage unit at the SNMP parser unit, the parsed data file.
[0015] Further, the performing, by the analysis unit at the SNMP parser unit, the delta analysis, based on the determined availability of the previous file related to the compressed raw data, further comprises assigning, by the analysis unit at the

SNMP parser unit, a raw value as a delta value in an event of determination of the non-existing status.
[0016] Further, the omit list comprises one or more of a node name, a host name, a
5 category name, and a counter name.
[0017] Further, the performing, by the analysis unit at the SNMP parser unit via the distributed computing clusters unit, the delta analysis, is done in parallel, by one or more distributed computing clusters in the distributed computing clusters unit. 10
[0018] Further, the storing, in the storage unit at the SNMP parser unit, the parsed data file, further comprises compressing, by the parser at the SNMP parser unit, the parsed data file.
15 [0019] Further, the performing, by the analysis unit at SNMP parser unit, the delta
analysis, based on the determined availability of the previous file related to the compressed raw data is done on the file system component.
[0020] Further, extracting, by the extraction unit at the SNMP parser unit at a
20 desired location, the raw data file from the compressed raw data.
[0021] Further, in an event the absent status of the previous file related to the
compressed raw data is determined by the extraction unit, the method comprises:
storing, in the storage unit at the SNMP parser unit, the raw data file extracted from
25 the compressed raw data.
[0022] Further, the available status is determined in an event the previous file related to the compressed raw data is available, and the absent status is determined in an event the previous file related to the compressed raw data is not available. 30
6

[0023] Further, in an event the non-existing status is determined for a target performance counter from the one or more performance counter, the method further comprises: adding, by the analysis unit at the SNMP parser unit, the target counter to the omit list. 5
[0024] The present invention disclosure also relates to a simple network management protocol (SNMP) parser unit for performing delta analysis. The SNMP parser unit comprises a transceiver unit configured to receive a compressed raw data from a file system component at a pre-defined interval of time, wherein the
10 raw data comprises one or more performance counters. The SNMP parser unit
further comprises an extraction unit connected to the transceiver unit, wherein the extraction unit is configured to determine one of: an available status and an absent status of a previous file related to the compressed raw data. Further, the SNMP parser unit comprises an analysis unit connected to the extraction unit, wherein the
15 analysis unit is configured to determine for each performance counter of the one or
more performance counters, an existence status of each performance counter in an omit list in an event of determination of the available status, wherein the existence status is one of: an existing status and a non-existing status, and wherein the existing status is determined in an event the performance counter is existing in the omit list,
20 and the non-existing status is determined in an event the performance counter is not
existing in the omit list. Further, the analysis unit is configured to perform a delta analysis for a subset of the one or more performance counters, wherein the subset of the one or more performance counters comprises a set of performance counters for which the non-existing status is determined. Further, the SNMP parser unit
25 comprises a parser connected to the analysis unit, wherein the parser is configured
to parse the raw data file from the compressed raw data based on the performance of the delta analysis, to generate a parsed data file, to generate a parsed data file. Thereafter, the SNMP parser unit comprises a storage unit connected to at least the parser, wherein the storage unit is configured to store the parsed data file.
30
7

[0025] Yet another aspect of the present disclosure relates to a user equipment (UE)
for performing delta analysis by a simple network management protocol (SNMP)
parser unit, the UE comprising a memory; and a processor coupled to the memory.
Further, the processor is configured to transmit to the SNMP parser unit, a
5 compressed raw data from a file system component at a pre-defined interval of time,
wherein the compressed raw data comprises one or more performance counters, and receive from the SNMP parser unit, a response comprising a parsed data file. The response is received based on determining, at the SNMP parser unit, one of: an available status and an absent status of a previous file related to the compressed raw
10 data. Further, the response is received based on determining, at the SNMP parser
unit, for each performance counter of the one or more performance counters, an existence status of each performance counter in an omit list in an event of determination of the available status, wherein the existence status is one of: an existing status and a non-existing status. Further, the response is received based on
15 performing, at the SNMP parser unit, a delta analysis for a subset of the one or more
performance counters, wherein the subset of the one or more performance counters comprises a set of performance counters for which the non-existing status is determined. Further, the response is received based on parsing, at the SNMP parser unit, a raw data file from the compressed raw data based on the performance of the
20 delta analysis, to generate the parsed data file. Further, the response is received
based on storing, at the SNMP parser unit, the parsed data file.
[0026] Yet another aspect of the present disclosure relates to a non-transitory computer-readable storage medium storing instruction for performing delta analysis
25 by a simple network management protocol (SNMP) parser unit, the storage medium
comprising executable code which, when executed by one or more units of the SNMP parser unit, causes a transceiver unit to receive at the SNMP parser unit, a compressed raw data from a file system component at a pre-defined interval of time, wherein the compressed raw data comprises one or more performance counters. The
30 executable code which, when executed causes an extraction unit to determine at the
8

SNMP parser unit, one of: an available status and an absent status of a previous file
related to the compressed raw data. Further, the executable code which, when
executed causes an analysis unit to determine at the SNMP parser unit, for each
performance counter of the one or more performance counters, an existence status
5 of each performance counter in an omit list in an event of determination of the
available status, wherein the existence status is one of: an existing status and a non-existing status. Further, the executable code which, when executed causes the analysis unit to perform at the SNMP parser unit, a delta analysis for a subset of the one or more performance counters, wherein the subset of the one or more
10 performance counters comprises a set of performance counters for which the non-
existing status is determined. Further, the executable code which, when executed causes by a parser to parse at the SNMP parser unit, a raw data file from the compressed raw data based on the performance of the delta analysis, to generate a parsed data file. Thereafter, the executable code which, when executed causes a
15 storage unit to store at the SNMP parser unit, the parsed data file.
BRIEF DESCRIPTION OF DRAWINGS
[0027] The accompanying drawings, which are incorporated herein, and constitute
20 a part of this disclosure, illustrate exemplary embodiments of the disclosed methods
and systems in which like reference numerals refer to the same parts throughout the
different drawings. Components in the drawings are not necessarily to scale,
emphasis instead being placed upon clearly illustrating the principles of the present
disclosure. Some drawings may indicate the components using block diagrams and
25 may not represent the internal circuitry of each component. It will be appreciated
by those skilled in the art that disclosure of such drawings includes disclosure of electrical components, electronic components or circuitry commonly used to implement such components.
9

[0028] FIG.1 illustrates an exemplary block diagram of a network performance management system [100], in accordance with the exemplary embodiments of the present invention.
5 [0029] FIG.2 illustrates an exemplary block diagram of a simple network
management protocol (SNMP) parser unit [200] for performing delta analysis, in accordance with exemplary embodiments of the present disclosure.
[0030] FIG.3 illustrates an exemplary method [300] flow diagram indicating the
10 process for performing delta analysis by a simple network management protocol
(SNMP) parser unit [200], in accordance with exemplary embodiments of the present disclosure.
[0031] FIG.4 illustrates an exemplary flowchart indicating a process for performing
15 delta analysis, in accordance with exemplary implementations of the present
disclosure.
[0032] FIG.5 illustrates an exemplary block diagram of a computing device upon which an embodiment of the present disclosure may be implemented. 20
[0033] FIG.6 illustrates an exemplary system architecture for performing delta analysis, in accordance with exemplary implementations of the present disclosure.
[0034] The foregoing shall be more apparent from the following more detailed
25 description of the disclosure.
DESCRIPTION
[0035] In the following description, for the purposes of explanation, various
30 specific details are set forth in order to provide a thorough understanding of
10

embodiments of the present disclosure. It will be apparent, however, that
embodiments of the present disclosure may be practiced without these specific
details. Several features described hereafter may each be used independently of one
another or with any combination of other features. An individual feature may not
5 address any of the problems discussed above or might address only some of the
problems discussed above.
[0036] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather,
10 the ensuing description of the exemplary embodiments will provide those skilled in
the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.
15
[0037] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, processes, and other components
20 may be shown as components in block diagram form in order not to obscure the
embodiments in unnecessary detail.
[0038] Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure
25 diagram, or a block diagram. Although a flowchart may describe the operations as
a sequential process, many of the operations may be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure.
30
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[0039] The word “exemplary” and/or “demonstrative” is used herein to mean
serving as an example, instance, or illustration. For the avoidance of doubt, the
subject matter disclosed herein is not limited by such examples. In addition, any
aspect or design described herein as “exemplary” and/or “demonstrative” is not
5 necessarily to be construed as preferred or advantageous over other aspects or
designs, nor is it meant to preclude equivalent exemplary structures and techniques
known to those of ordinary skill in the art. Furthermore, to the extent that the terms
“includes,” “has,” “contains,” and other similar words are used in either the detailed
description or the claims, such terms are intended to be inclusive—in a manner
10 similar to the term “comprising” as an open transition word—without precluding
any additional or other elements.
[0040] As used herein, an “electronic device”, or “portable electronic device”, or “user device” or “communication device” or “user equipment” or “device” refers
15 to any electrical, electronic, electromechanical and computing device. The user
device is capable of receiving and/or transmitting one or parameters, performing function/s, communicating with other user devices and transmitting data to the other user devices. The user equipment may have a processor, a display, a memory, a battery and an input-means such as a hard keypad and/or a soft keypad. The user
20 equipment may be capable of operating on any radio access technology including
but not limited to IP-enabled communication, Zig Bee, Bluetooth, Bluetooth Low Energy, Near Field Communication, Z-Wave, Wi-Fi, Wi-Fi direct, etc. For instance, the user equipment may include, but not limited to, a mobile phone, smartphone, virtual reality (VR) devices, augmented reality (AR) devices, laptop,
25 a general-purpose computer, desktop, personal digital assistant, tablet computer,
mainframe computer, or any other device as may be obvious to a person skilled in the art for implementation of the features of the present disclosure.
[0041] Further, the user device may also comprise a “processor” or “processing
30 unit” includes processing unit, wherein processor refers to any logic circuitry for
12

processing instructions. The processor may be a general-purpose processor, a
special purpose processor, a conventional processor, a digital signal processor, a
plurality of microprocessors, one or more microprocessors in association with a
DSP core, a controller, a microcontroller, Application Specific Integrated Circuits,
5 Field Programmable Gate Array circuits, any other type of integrated circuits, etc.
The processor may perform signal coding data processing, input/output processing, and/or any other functionality that enables the working of the system according to the present disclosure. More specifically, the processor is a hardware processor.
10 [0042] As portable electronic devices and wireless technologies continue to
improve and grow in popularity, the advancing wireless technologies for data transfer are also expected to evolve and replace the older generations of technologies. In the field of wireless data communications, the dynamic advancement of various generations of cellular technology are also seen. The
15 development, in this respect, has been incremental in the order of second generation
(2G), third generation (3G), fourth generation (4G), and now fifth generation (5G), and more such generations are expected to continue in the forthcoming time.
[0043] As used herein, “storage unit” or “memory unit” refers to a machine or
20 computer-readable medium including any mechanism for storing information in a
form readable by a computer or similar machine. For example, a computer-readable
medium includes read-only memory (“ROM”), random access memory (“RAM”),
magnetic disk storage media, optical storage media, flash memory devices or other
types of machine-accessible storage media. The storage unit stores at least the data
25 that may be required by one or more units of the system to perform their respective
functions.
[0044] As discussed in the background section, the current known solutions for
performing delta calculations have several shortcomings such as those related to
30 time consumption and resource consumption due to manual interventions, etc.
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[0045] The present disclosure aims to overcome the above-mentioned and other
existing problems in this field of technology by providing a Simple Network
Management Protocol (SNMP) Parser which processes a raw network performance
5 data and calculates a delta, or the difference, as compared to the previous data that
is received from one or more network nodes a base station, an access point (AP), etc. The present solution processes the raw network performance data received from the one or more network nodes at a pre-defined interval of time, for example, once every 15 min., etc. Also, as disclosed by the present solution the difference may be
10 calculated as and when the raw network performance data is provided to the SNMP
parser. This means that the delta calculation is done in real-time, without the need to wait for a specific time period or interval. The present solution utilizes a distributed computing via which the SNMP Parser may process the raw network performance data and calculate the delta in a more parallelized and efficient
15 manner. This approach allows for faster processing times associated with the raw
network performance data and enables the SNMP Parser to handle large volumes of the raw network performance data effectively.
[0046] Hereinafter, exemplary embodiments of the present disclosure will be
20 described with reference to the accompanying drawings.
[0047] FIG.1 illustrates an exemplary block diagram of a network performance management system [100], in accordance with the exemplary embodiments of the present invention. Referring to Figure 1, the network performance management
25 system [100] comprises various sub-systems such as: integrated performance
management system [101], normalization layer/ system [121], computation layer/ system [116], anomaly detection layer/ system [115], streaming engine [118], load balancer system [119], operations and management system [113], service quality Manager/system [114], Correlation Engine [117], API gateway system [120],
30 analysis engine [112], parallel computing framework [111], forecasting engine
14

[102], distributed file system [103], mapping layer/ system [104], distributed data
lake/system [105], scheduling layer/ system [106], reporting engine [107], message
broker/system [108], graph layer/ system [109], and caching layer/ system [110].
The connections between these subsystems are also as shown in FIG 1. However,
5 it will be appreciated by those skilled in the art that the present disclosure is not
limited to the connections shown in the diagram, and any other connections between various subsystems that are needed to realise the effects are within the scope of this disclosure.
10 [0048] 5G Performance Management Engine: The 5G Performance management
engine will gather and process performance counter data from different data sources and based on the aggregation required store the network performance data in Distributed Data Lake.
15 [0049] This component is responsible for all reporting and visualization of
Performance counter data.
[0050] 5G Key Performance Indicator (KPI) Engine: The 5G Key Performance
Indicator (KPI) Engine responsible for managing all the KPI of all the network
20 elements. Counters collected and processed by 5G Performance management
engine different data sources will be used by KPI engine to calculate the KPI and segregate it based on the aggregation required and store KPI data in Distributed Data Lake.
25 [0051] This component is responsible for all reporting and visualization of KPI
data.
[0052] Ingestion layer: The objective for designing the Ingestion layer to define an environment which is capable of ingesting various types of incoming data such
15

as Alarms, Counter, Configuration, CDRs, Infra-metric data, Logs and Inventory data.
[0053] Data Ingestion Layer gathers data and forwards it to the data processing
5 systems. The data ingestion layer processes incoming data, validating data, and
routing it to the Normalization layer, Streaming Engine [118], Streaming Analytics and Message brokers based on the requirements for further analytics.
[0054] Normalization layer [121]: The data normalization layer [121] normalize,
10 enrich and store data in database. Normalizer layer insert normalized data into
various database: Distributed Data Lake [105], Caching Layer [110] and Graph
layer [109]. It produces data for Message Broker. Normalization Layer is also
responsible for providing the normalized data to another sub-system. These sub¬
systems are Analysis Engine [112], Correlation Engine [117], Service Quality
15 Manager [114] and Streaming Engine [118]. Normalization Layer is also
responsible for providing the normalized data to another sub-system. These sub-systems are Analysis Engine [112], Correlation Engine [117], Service Quality Manager [114] and Streaming Engine [118].
20 [0055] Caching layer [110]: The data normalization layer normalize, enrich and
store data in database. Normalizer layer [121] insert normalized data into various database: Distributed Data Lake [105], Caching Layer [110] and Graph layer [109]. It produces data for Message Broker [108].
25 [0056] Computation layer 116]: The data normalization layer normalize, enrich
and store data in database. Normalizer layer insert normalized data into various database: Distributed Data Lake [105], Caching Layer [110] and Graph layer [109]. It produces data for Message Broker [108].
16

[0057] Message broker [108]: Message Broker [108] is publish–subscribe
messaging system, which manages and maintains the real-time stream of data from
different applications. It enables communication between producers and consumers
using message-based topics. It designs a platform for high-end new-generation
5 distributed applications. Message Broker [108] permits large number of permanent
or ad-hoc consumers. Message Brokers [108] relies on the file-system for storage and caching purposes, thus it is fast. It prevents data loss and is fault-tolerant.
[0058] Graph layer [109]: Relationship Modeler can model the
10 alarm/counter/configuration/CDR Data/ Infra-metric data/5G Probe Data and
Inventory data. The modeler should be capable of building the relationship among
the various type of data provision in the model at its end. For example, Relationship
modeler is able to model Alarm and Counter data or probe and Alarm data and their
relationship with each other. The modeler should be capable of processing the steps
15 provisioned in the model and provide the outcome to requested system, which can
be Parallel Computing system /Workflow Engine /Query engine /correlation system/5G Performance management engine/5G KPI engine.
[0059] Scheduling layer [106]: Scheduling Layer will be capable of running tasks
20 at pre-defined intervals of time configured as per user choice. A task can be an
activity, which performs a service call, an API call to another micro service, an execution of an elastic search query and storing its output in DDL or DFS or sending it to another micro-service. Scheduling Layer also facilitates graph traversals via Mapping Layer to execute tasks. 25
[0060] Analysis Engine [112]: The objective for designing the Analysis Engine is
to define the environment where we can configure and execute the workflow (Set
of tasks) for any use-cases to debug or better understanding of the call flow. User
can also query upon the data coming from different sub-systems or external
30 gateway for better overview of the data or identify the actual issue present on the
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data. User can also configure the set of polices through which user can identify the anomaly present on the data and can receive the notification once policy breached or some abnormal behaviour occurs.
5 [0061] Parallel Computing Framework [111]: The Parallel Computing
Framework provides a platform for executing computing tasks in parallel, enhancing processing speeds and resource management. It supports the creation of task chains and allows for the simultaneous execution of multiple workflows.
10 [0062] Distributed File System [103]: The Distributed File System [103] is a
centralized, scalable, and flexible storage solution that holds large amounts of raw data in its native format. This repository allows for easy access and further analysis of the data, supporting various analytical and processing needs of the system.
15 [0063] Load Balancer System [119]: The Load balancing refers to efficiently
distributing incoming network traffic across a group of backend servers, also known as a server farm or server pool. The Load balancer routes all the traffic on the servers and sends the client requests across the micro services capable of fulfilling those requests. ELB can route the request based on round robin scheduling, header-based
20 request dispatch, and context-based request dispatch. In header-based request
dispatch ESLB handles event and event acknowledgement and forwards the request/response to the specific micro service which has requested for the event.
[0064] Streaming Engine [118]: The streaming Engine [118] will receive the data
25 from connected sub-systems and stream the received data to UI in support with
Distributed Data Lake, Message Broker and Caching layer. Stream Analytics will
receive data from the sub-systems and perform the required computation on data in
real time followed by sending it to UI. Streaming Engine [118] and Stream
Analytics will stream data from Distributed Data Lake, Message Broker, and
30 Caching layer according to the requirement and will stream data to UI in real time.
18

[0065] Reporting Engine [107]: The Reporting Engine [107] is a key subsystem
of the network performance management system [100]. The fundamental purpose
of designing the Reporting Engine [107] is to dynamically create report layouts of
5 API data, catered to individual client requirements, and deliver these reports via the
Notification Engine. The REM serves as the primary interface for creating custom reports based on the data visualized through the client's dashboard. These custom dashboards, created by the client through the User Interface (UI), provide the basis for the Reporting Engine [107] to process and compile data from various interfaces.
10 The main output of the Reporting Engine [107] is a detailed report generated in
spreadsheet format. The Reporting Engine’s [107] unique capability to parse data from different subsystem interfaces, process it according to the client's specifications and requirements, and generate a comprehensive report makes it an essential component of this performance management system. Furthermore, the
15 Reporting Engine [107] integrates seamlessly with the Notification Engine to
ensure timely and efficient delivery of reports to clients via email, ensuring the information is readily accessible and usable, thereby improving overall client satisfaction and system usability.
20 [0066] Correlation Engine [117]: The Correlation Engine [117] is a component
that identifies and understands relationships within data. It processes data from various sources to detect patterns, trends, and associations that might not be immediately apparent. This engine helps in recognizing how different metrics or events are interconnected, which is essential for diagnosing issues and optimizing
25 performance.
[0067] API Gateway System [120]: The API Gateway System [120] acts as a
reverse proxy to accept all application programming interface (API) calls, aggregate
the various services required to fulfil them, and return the appropriate result. It is
30 crucial for managing, securing, and monitoring API traffic between the clients and
backend services.
19

[0068] Operation and Management System [113]: This component is responsible
for the overall operation and management of the system. It includes tasks such as
monitoring system health, managing resources, deploying updates, and ensuring the
5 continuous and smooth operation of the performance management system.
[0069] Service Quality Manager/System [114]: The Service Quality Manager
[114] ensures that the quality of service (QoS) standards are met. It assesses and
maintains the quality of the services provided by the system, making sure that
10 performance metrics are within acceptable ranges and addressing any issues that
may arise to ensure consistent service delivery.
[0070] Forecasting Engine [102]: The Forecasting Engine [102] uses historical
data to predict future trends and performance metrics. This component helps in
15 proactive planning and decision-making by providing insights into potential future
states of the system based on current and past data.
[0071] Referring to Figure 2, an exemplary of a simple network management
protocol (SNMP) parser unit [200] for performing delta analysis is shown, in
20 accordance with the exemplary embodiments of the present invention. Also, all of
the components/ units of the SNMP parser unit [200] are assumed to be connected to each other unless otherwise indicated below.
[0072] Further, in accordance with the present disclosure, it is to be acknowledged
25 that the functionality described for the various components/units can be
implemented interchangeably. While specific embodiments may disclose a
particular functionality of these units for clarity, it is recognized that various
configurations and combinations thereof are within the scope of the disclosure. The
functionality of specific units as disclosed in the disclosure should not be construed
30 as limiting the scope of the present disclosure. Consequently, alternative
20

arrangements and substitutions of units, provided they achieve the intended functionality described herein, are considered to be encompassed within the scope of the present disclosure
5 [0073] The SNMP parser unit [200] is configured for performing delta analysis,
with the help of the interconnection between the components/units of the SNMP parser unit [200]. The Simple Network Management Protocol (SNMP) parser unit [200] is a component of a network management system that is responsible for interpreting and processing SNMP messages received from managed network
10 devices. The SNMP messages is commonly used for monitoring and managing
network devices such as routers, switches, and servers. The person skilled in the art would appreciate that the description of Simple Network Management Protocol (SNMP) parser unit [200] provided above is more mere understanding and the same should not be interpreted in a manner to limit the scope of the present disclosure.
15
[0074] Further, the SNMP parser unit [200] comprises a transceiver unit [200a] configured to receive a compressed raw data from a file system component [204] at a pre-defined interval of time, wherein the raw data comprises one or more performance counters. In an implementation of the present solution, the pre-defined
20 interval of time may one of a preconfigured interval of time such as 15 mins, 30
mins etc. or a dynamically configured interval of time to implement the present solution. The term ‘transceiver unit’ is a combined transmitter and receiver component used in systems to facilitate the transmission and reception of signals. This component receives the compressed raw data from the file system component
25 [204] at the predefined interval of time. It is emphasized that the compressed raw
data comprises the one or more performance counters associated with a wireless communications network.
[0075] As used herein, the “performance counters” refers to metrics used to
30 measure and analyse the performance and behaviour of the network elements.
21

Further, the delta analysis may refer to a process of analysing changes in the metrics
over a specific period, typically comparing current values associated with the
network elements to historical values associated with the network elements.
Further, the performance counters in may include a throughput (bytes per second)
5 counter, a packet loss counter, a latency counter, a network utilization counter, an
error rates counter, a response time counter, a connection establishment time counter, a bandwidth usage counter, any other like such counter that may be appreciated by a person skilled in the art as necessary to implement the present disclosure.
10
[0076] In a preferred implementation of the present solution, the raw data is received in a predefined format such as a zip format. Said compressed raw data may be a network management related data and may be generated by devices and/ or network components that are associated with the wireless communications network.
15
[0077] The SNMP parser unit [200] is further comprise an extraction unit [200b] connected to at least the transceiver unit [200a]. Further, the extraction unit [200b] is configured to determine one of an available status and an absent status of a previous file related to the compressed raw data. Further, the extraction unit [200b]
20 is further configured to extract, at a desired location, the raw data file from the
compressed raw data. In an exemplary implementation of the present disclosure, the system comprises performing a task on the compressed raw data received in the predefined format such as unzipping the file at the desired location where a previous file associated with a previous time interval (with respect to a time interval
25 associated with the compressed raw data) the was collected and analysed by the
SNMP parser unit [200]. Further, in an event the previous file associated with the previous time interval is not available, the compressed raw data is unzipped/extracted and analysed at the location of collection or receival of the data. The available status of the previous file related to the compressed raw data is
30 determined by the extraction unit [200b] in an event the previous file related to the
22

compressed raw data is available, and the absent status is determined. The absent
status of the previous file related to the compressed raw data is determined by the
extraction unit [200b] in an event the previous file related to the compressed raw
data is not available. Further, in an event the absent status of the previous file related
5 to the compressed raw data is determined by the extraction unit [200b], the
compressed raw data may be assigned a raw value as a delta value.
[0078] The SNMP parser unit [200] is further comprises analysis unit [200c] connected to the extraction unit [200b]. Further, the analysis unit [200c] is
10 configured to determine for each performance counter of the one or more
performance counters, an existence status of each performance counter in an omit list in an event of determination of the available status, wherein the existence status is one of an existing status and a non-existing status, and wherein the existing status is determined in an event the performance counter is existing in the omit list, and
15 the non-existing status is determined in an event the performance counter is not
existing in the omit list. In an implementation of the present disclosure, the ‘analysis unit’ the existence status of each performance counter, i.e., checking if they are present in an omit list, wherein the omit list comprises one or more of a node name, a host name, a category name, and a counter name.
20
[0079] In an example, node name refers to the specific name or identifier of a network node, such as Node_A" or "Router_1. The host’s name may indicate the name of a host machine or server, such as Host_123 or Server_XYZ. The category name may be group performance counters based on their function or relevance, like
25 Traffic_Metrics or Error_Stats. The counter name refers an individual counters
under a category could be named to reflect their specific metric, such as Packet_Loss_Rate, CPU_Usage, or Network_Latency.
[0080] Further, the analysis unit [200c] is configured to perform a delta analysis
30 for a subset of the one or more performance counters, wherein the subset of the one
23

or more performance counters comprises a set of performance counters for which
the non-existing status is determined by the analysis unit [200c]. Further, the
analysis unit [200c] in accordance with present disclosure is configured to perform
the delta analysis, based on the determined availability of the previous file related
5 to the compressed raw data, on the file system component [204]. As disclosed by
the present disclosure, in an event a non-existing status is determined by the analysis
unit [200c] for a performance counter i.e., a target performance counter from the
one or more performance counter, in said event the analysis unit [200c] is further
configured to add said target performance counter to the omit list. In an
10 implementation of the present disclosure, the analysis unit [200c] is configured to
perform via the distributed computing clusters unit [202], the delta analysis in a parallel manner, by one or more distributed computing clusters in the distributed computing clusters unit [202].
15 [0081] The SNMP parser unit [200] is further comprises a parser [200d] connected
to the analysis unit [200c]. Further, the parser [200d] is configured to parse a raw data file from the compressed raw data based on the performance of the delta analysis, to generate a parsed data file. In an implementation of the present solution, the extraction unit [200b] is further configured to extract, at a desired location, the
20 raw data file from the compressed raw data. Further, the parser [200d] processes
the raw data file based on the results of the delta analysis performed by the analysis unit [200c]. The parser [200d] parses the raw data file to extract relevant information and then the parser [200d] may further formats it for further processing and storage.
25
[0082] In an example, the delta analysis improves the efficiency of parsing raw data into generated parsed data by only focusing on the performance counters that have changed since the last analysis. When the SNMP parser unit [200] receives compressed raw data, it first checks if a previous file related to this data exists. If
24

the previous file is available, it identifies which performance counters are new or have changed by comparing them against an omit list.
[0083] By performing delta analysis, the SNMP parser unit only processes the
5 subset of performance counters that are not in the omit list, reducing the amount of
data that needs to be parsed and stored.
[0084] Further, the SNMP parser unit [200] is comprises a storage unit [200e] connected to at least the parser [200d], wherein the storage unit [200e] configured
10 to store the parsed data file. Further, the storage unit [200e] is configured to store
the parsed data file, is further configured to compress, by the parser [200d], the parsed data file. Furthermore, in an event the absent status of the previous file related to the compressed raw data is determined by the extraction unit [200b], the storage unit [200e] is configured to store the raw data file extracted from the
15 compressed raw data.
[0085] Referring to Figure 3, a method [300] flow diagram indicating the process
for performing delta analysis by a simple network management protocol (SNMP)
parser unit [200], is shown in accordance with exemplary embodiments of the
20 present disclosure is shown. As shown in Figure 3, the method [300] starts at step
[302].
[0086] At step [304], the method as disclosed by the present disclosure comprises, receiving, by a transceiver unit [200a] at the SNMP parser unit [200], a compressed
25 raw data from a file system component [204] at a pre-defined interval of time,
wherein the compressed raw data comprises one or more performance counters. The term ‘transceiver unit’ is a combined transmitter and receiver component used in systems to facilitate the transmission and reception of signals. This component receives compressed raw data from a file system component [204] at predefined
30 intervals. It is emphasized that the raw data comprises one or more performance
25

counters. The compressed raw data is received in predefined format such as a zip
format. This raw compressed data may be network management related data and
may be generated by devices/components that are installed in the wireless
communications network.
5
[0087] In an example, the performance counters are the data points collected to
monitor and evaluate the performance of various network elements. These counters
can include information such as traffic volume, error rates, latency, and resource
utilization.
10
[0088] At next step [306], the method as disclosed by the present disclosure comprises, determining, by an extraction unit [200b] at the SNMP parser unit [200], one of: an available status and an absent status of a previous file related to the compressed raw data. In an implementation of the present disclosure, in an event
15 the compressed raw data filed is received in the predefined zip format the solution
comprises unzipping the compressed raw data at a desired location where the data of a previous interval i.e., the previous file related to the compressed raw data was collected and analysed by the SNMP parser unit [200]. Further, in an event the previous file related to the compressed raw data for the previous interval is not
20 available, the data is unzipped/extracted and analysed at a predefined location and
in a predefined manner. The available status is determined by the extraction unit [200b] in an event the previous file related to the compressed raw data is available, and the absent status is determined by the extraction unit [200b]in an event the previous file related to the compressed raw data is not available. In an event, the
25 absent status of the previous file related to the compressed raw data is determined
by the extraction unit [200b], the solution further comprises assigning, by the analysis unit [200c] at the SNMP parser unit [200], a raw value as a delta value in an event of determination of the non-existing status.
30 [0089] At next step [308], the method as disclosed by the present disclosure
comprises, determining, by an analysis unit [200c] at the SNMP parser unit [200],
26

for each performance counter of the one or more performance counters, an existence
status of each performance counter in an omit list in an event of determination of
the available status, wherein the existence status is one of: an existing status and a
non-existing status, and wherein the existing status is determined in an event the
5 performance counter is existing in the omit list, and the non-existing status is
determined in an event the performance counter is not existing in the omit list. In an implementation of the present disclosure, the ‘analysis unit’ determines the existence status of each performance counter by checking if they are present in an omit list, wherein the omit list comprises one or more of a node name, a host name,
10 a category name, and a counter name. As disclosed by the present disclosure, the
solution further comprises the performing, by the analysis unit [200c] at SNMP parser unit [200], the delta analysis, based on the determined availability of the previous file related to the compressed raw data is done on the file system component [204].
15
[0090] In an example, node name refers to the specific name or identifier of a network node, such as Node_A" or "Router_1. The host’s name may indicate the name of a host machine or server, such as Host_123 or Server_XYZ. The category name may be group performance counters based on their function or relevance, like
20 Traffic_Metrics or Error_Stats. The counter name refers an individual counters
under a category could be named to reflect their specific metric, such as Packet_Loss_Rate, CPU_Usage, or Network_Latency.
[0091] At next step [310], the method as disclosed by the present disclosure
25 comprises, performing, by the analysis unit [200c] at the SNMP parser unit [200],
a delta analysis for a subset of the one or more performance counters, wherein the
subset of the one or more performance counters comprises a set of performance
counters for which the non-existing status is determined. Further, the analysis unit
[200c] perform the delta analysis, based on the determined availability of the
30 previous file related to the compressed raw data, on the file system component
27

[204]. As disclosed by the present disclosure, in an event a non-existing status is
determined by the analysis unit [200c] for a performance counter i.e., a target
performance counter from the one or more performance counter, in said event the
method [300] further comprises: adding, by the analysis unit [200c] at the SNMP
5 parser unit [200], the target counter to the omit list. The analysis unit [200c] is
configured for the performing, at the SNMP parser unit [200] via a distributed computing clusters unit [202], the delta analysis, is done in parallel, by one or more distributed computing clusters in the distributed computing clusters unit [202].
10 [0092] At next step [312], the method as disclosed by the present disclosure
comprises, parsing, by a parser unit [200d] at the SNMP parser unit [200], a raw data file from the compressed raw data based on the performance of the delta analysis, to generate a parsed data file. In an implementation of the present solution, the solution further comprises extracting, by the extraction unit [200b] at the SNMP
15 parser unit [200] at a desired location, the raw data file from the compressed raw
data. Further, the parser [200d] processes the raw data file based on the results of the delta analysis performed by the analysis unit [202c]. The parser [200d] parses the raw data file to extract relevant information and then the parser [200d] may further formats it for further processing and storage.
20
[0093] In an example, the delta analysis improves the efficiency of parsing raw data into generated parsed data by only focusing on the performance counters that have changed since the last analysis. When the SNMP parser unit [200] receives compressed raw data, it first checks if a previous file related to this data exists. If
25 the previous file is available, it identifies which performance counters are new or
have changed by comparing them against an omit list.
[0094] By performing delta analysis, the SNMP parser unit only processes the
subset of performance counters that are not in the omit list, reducing the amount of
30 data that needs to be parsed and stored.
28

[0095] At last step [314], the method as disclosed by the present disclosure
comprises, storing, in a storage unit [200e] at the SNMP parser unit [200], the
parsed data file. Further, as disclosed by the present disclosure, the solution
comprises the storing, in the storage unit [200e] at the SNMP parser unit [200], the
5 parsed data file further comprises compressing, by the parser [200d] at the SNMP
parser unit [200], the parsed data file. Furthermore, in an event the absent status of the previous file related to the compressed raw data is determined by the extraction unit [200b], the method [300] comprises storing, in the storage unit [200e] at the SNMP parser unit [200], the raw data file extracted from the compressed raw data. 10
[0096] Thereafter, the method [316] terminates at step [S318].
[0097] FIG.4 illustrates an exemplary flowchart indicating a process [400] for
performing delta analysis, in accordance with exemplary implementations of the
15 present disclosure.
[0098] The process [400] starts with S1, a block labelled "Raw 4G/5G network performance data in (zip file)". This indicates that the data comes in as a zipped file.
20 [0099] Next, at S2, the process [400] moves to a block labelled Previous File
Check: The flowchart then asks if a "Previous file for 4G/5G network performance data exist or not". This means the system checks if there's already a file containing performance data from the network.
25 [0100] In a case the system check generates a response of Yes i.e., If there is a
previous file, the process [400] moves S3 to an action box that says, "Omit List contains data or not". Omit List here likely refers to a list of data points that should be excluded from processing for some reason. In a case the system check generates a response of NO i.e., If there is no previous file, the process [400] goes to S4 a box
30 labelled at the block labelled Previous File Check the solution writes data directly
29

to the file system component [204] which means this initial data is used to create a new file.
[0101] Yes: If the Omit List contains data, the process [400] moves to S5, a box
5 labelled "Onit data" which means the current data is likely appended to the existing
file.
[0102] In a case the system check generates a No i.e., if the Omit List doesn't
contain data, the process [400] goes to S6, an action box labelled "SNMP parser
10 (delta calculation)". SNMP (Simple Network Management Protocol) is a protocol
for managing network devices. Delta calculation refers to the difference between two values. In this context, it likely means calculating the difference between the current data and the previous data to isolate changes in network performance.
15 [0103] Enriched Data: After the SNMP parsing and delta calculation, the data is
described as "Enriched data at particular bucket level (zip file)". This suggests the data is processed to a more usable format, possibly focused on specific areas or timeframes (buckets). The data is then stored in a file system component [204] again.
20
[0104] The process [400] ends with S7, the enriched data being stored in the file system component [204].
[0105] Fig.5 illustrates an exemplary block diagram of a computing device [500]
25 upon which an embodiment of the present disclosure may be implemented. In an
implementation, the computing device [500] implements the method [300] for
managing one or more supplementary services in a multi-network environment by
utilising network performance management system [100]. In another
implementation, the computing device [500] itself implements the method [300] for
30 managing one or more supplementary services in a multi-network environment
30

using one or more units configured within the computing device [500], wherein said one or more units are capable of implementing the features as disclosed in the present disclosure.
5 [0106] The computing device [500] may include a bus [502] or other
communication mechanism for communicating information, and a hardware processor [504] coupled with the bus [502] for processing information. The hardware processor [504] may be, for example, a general-purpose microprocessor. The computing device [500] may also include a main memory [506], such as a
10 random-access memory (RAM), or other dynamic storage device, coupled to the
bus [502] for storing information and instructions to be executed by the processor [504]. The main memory [506] also may be used for storing temporary variables or other intermediate information during execution of the instructions to be executed by the processor [504]. Such instructions, when stored in non-transitory storage
15 media accessible to the processor [504], render the computing device [500] into a
special-purpose machine that is customized to perform the operations specified in the instructions. The computing device [500] further includes a read only memory (ROM) [508] or other static storage device coupled to the bus [502] for storing static information and instructions for the processor [504].
20
[0107] A storage device [510], such as a magnetic disk, optical disk, or solid-state drive is provided and coupled to the bus [502] for storing information and instructions. The computing device [500] may be coupled via the bus [502] to a display [512], such as a cathode ray tube (CRT), for displaying information to a
25 computer user. An input device [514], including alphanumeric and other keys, may
be coupled to the bus [502] for communicating information and command selections to the processor [504]. Another type of user input device may be a cursor controller [516], such as a mouse, a trackball, or cursor direction keys, for communicating direction information and command selections to the processor
30 [504], and for controlling cursor movement on the display [512]. This input device
31

typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allow the device to specify positions in a plane.
[0108] The computing device [500] may implement the techniques described
5 herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware
and/or program logic which in combination with the computing device [500] causes or programs the computing device [500] to be a special-purpose machine. According to one embodiment, the techniques herein are performed by the computing device [500] in response to the processor [504] executing one or more
10 sequences of one or more instructions contained in the main memory [506]. Such
instructions may be read into the main memory [506] from another storage medium, such as the storage device [510]. Execution of the sequences of instructions contained in the main memory [506] causes the processor [504] to perform the process steps described herein. In alternative embodiments, hard-wired circuitry
15 may be used in place of or in combination with software instructions.
[0109] The computing device [500] also may include a communication interface [528] coupled to the bus [502]. The communication interface [528] provides a two-way data communication coupling to a network link [520] that is connected to a
20 local network [522]. For example, the communication interface [528] may be an
integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, the communication interface [528] may be a local area network (LAN) card to provide a data communication connection to a
25 compatible LAN. Wireless links may also be implemented. In any such
implementation, the communication interface [528] sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.
32

[0110] The computing device [500] can send messages and receive data, including
program code, through the network(s), the network link [520] and the
communication interface [528]. In the Internet example, a server [530] might
transmit a requested code for an application program through the Internet [528], the
5 ISP [526], the host [524], the local network [522] and the communication interface
[528]. The received code may be executed by the processor [504] as it is received, and/or stored in the storage device [510], or other non-volatile storage for later execution.
10 [0111] Referring to FIG.6, an exemplary system architecture [600] for performing
delta analysis, in accordance with exemplary implementations of the present disclosure.
[0112] File System Component [204]: A storage system where large volumes of
15 raw data are stored. This raw data is in a compressed format and includes
performance counters from network devices. Also, after the delta calculation and parsing, the processed (parsed) data is stored back into the file system Component [204]
20 [0113] Delta Calculation: This unit is responsible for performing delta analysis on
the raw data. The delta calculation involves comparing new data with previous data to identify changes or updates. This reduces the amount of data that needs to be processed.
25 [0114] Distributed Computing Clusters Unit [202]: The computation master
coordinates the delta analysis process across multiple worker nodes. These workers process data in parallel, which enhances performance and efficiency.
[0115] The transceiver unit [200a] receives compressed raw data from the file
30 system at predefined intervals. This data includes performance counters relevant to
33

network performance. Further, the extraction unit [200b] determines the availability
of previous files and extracts raw data from the compressed files. If the previous
file is not available, it assigns the raw data a delta value and processes it
accordingly.
5
[0116] Further, the analysis unit [200c] checks performance counters against an
omit list to determine which counters are new or have changed. It performs delta
analysis on the subset of performance counters that are not in the omit list. This unit
operates in parallel using the distributed computing clusters unit [202]. Then parses
10 the raw data based on the delta analysis to generate parsed data files. This parsed
data is then ready for further processing or storage by the storage unit [200e]. After
that stores the parsed data files in the file system component [204]. If no previous
file is available, it stores the raw data extracted from the compressed files.
15 [0117] Yet another aspect of the present disclosure relates to a user equipment (UE)
for performing delta analysis by a simple network management protocol (SNMP) parser unit [200], the UE comprising a memory; and a processor coupled to the memory. Further, the processor is configured to transmit to the SNMP parser unit [200], a compressed raw data from a file system component [204] at a pre-defined
20 interval of time, wherein the compressed raw data comprises one or more
performance counters, and receive from the SNMP parser unit [200], a response comprising a parsed data file. The response is received based on determining, at the SNMP parser unit [200], one of: an available status and an absent status of a previous file related to the compressed raw data. Further, the response is received
25 based on determining, at the SNMP parser unit [200], for each performance counter
of the one or more performance counters, an existence status of each performance counter in an omit list in an event of determination of the available status, wherein the existence status is one of: an existing status and a non-existing status. Further, the response is received based on performing, at the SNMP parser unit [200], a delta
30 analysis for a subset of the one or more performance counters, wherein the subset
of the one or more performance counters comprises a set of performance counters
34

for which the non-existing status is determined. Further, the response is received
based on parsing, at the SNMP parser unit [200], a raw data file from the
compressed raw data based on the performance of the delta analysis, to generate the
parsed data file. Further, the response is received based on storing, at the SNMP
5 parser unit [200], the parsed data file.
[0118] Yet another aspect of the present disclosure relates to a non-transitory computer-readable storage medium storing instruction for performing delta analysis by a simple network management protocol (SNMP) parser unit [200], the storage
10 medium comprising executable code which, when executed by one or more units
of the SNMP parser unit [200], causes a transceiver unit [200a] to receive at the SNMP parser unit [200], a compressed raw data from a file system component [204] at a pre-defined interval of time, wherein the compressed raw data comprises one or more performance counters. The executable code which, when executed causes
15 an extraction unit [200b] to determine at the SNMP parser unit [200], one of: an
available status and an absent status of a previous file related to the compressed raw data. Further, the executable code which, when executed causes an analysis unit [200c] determine at the SNMP parser unit [200], for each performance counter of the one or more performance counters, an existence status of each performance
20 counter in an omit list in an event of determination of the available status, wherein
the existence status is one of: an existing status and a non-existing status. Further, the executable code which, when executed causes the analysis unit [200c] to perform at the SNMP parser unit [200], a delta analysis for a subset of the one or more performance counters, wherein the subset of the one or more performance
25 counters comprises a set of performance counters for which the non-existing status
is determined. Further, the executable code which, when executed causes by a parser [200d] to parse at the SNMP parser unit [200], a raw data file from the compressed raw data based on the performance of the delta analysis, to generate a parsed data file. Thereafter, the executable code which, when executed causes a
30 storage unit [200e] to store at the SNMP parser unit [200], the parsed data file.
35

[0119] As is evident from the above, the present disclosure provides a technically
advanced solution for performing delta analysis in a wireless communication
network for determining network performance. The solution enables users to
perform targeted computations and analysis, which allowing users to extract
5 relevant insights without having to sift through vast amounts of irrelevant data for
determining the wireless communication network performance. This targeted approach minimizes the time and effort required for data interpretation and focusing only on the relevant data for a specific time period which enables users to optimize resource allocation by identifying periods of high demand or inefficiency associated
10 with the wireless communication network. Further, the solution facilitates more
accurate evaluations since the users can filter out irrelevant data and pinpoint the root causes of issues more effectively which is responsible for affecting the performance in wireless communication network. By analysing peak usage times, users can optimize resource allocation and enables informed decision-making
15 regarding network management and upgrades.Further, implementing the features
of the solution enables one to save resources and reduce time involved in performing computation and analysis of the performance counters associated with the wireless communication network by focusing on specific time periods, further the users can streamline the analysis process by narrowing down the data scope,
20 thereby reducing the amount of data that needs to be processed for achieving the
desired result. This results in faster computation times and less strain on computational resources for determining network performance of the wireless communication network.
25 [0120] While considerable emphasis has been placed herein on the disclosed
embodiments, it will be appreciated that many embodiments can be made and that many changes can be made to the embodiments without departing from the principles of the present disclosure. These and other changes in the embodiments of the present disclosure will be apparent to those skilled in the art, whereby it is to
36

be understood that the foregoing descriptive matter to be implemented is illustrative and non-limiting.

We Claim:
1. A method for performing delta analysis by a simple network management
protocol (SNMP) parser unit [200], the method comprising:
- receiving, by a transceiver unit [200a] at the SNMP parser unit [200], a compressed raw data from a file system component [204] at a pre-defined interval of time, wherein the compressed raw data comprises one or more performance counters;
- determining, by an extraction unit [200b] at the SNMP parser unit [200], one of: an available status and an absent status of a previous file related to the compressed raw data;
- determining, by an analysis unit [200c] at the SNMP parser unit [200], for each performance counter of the one or more performance counters, an existence status of each performance counter in an omit list in an event of determination of the available status, wherein the existence status is one of: an existing status and a non-existing status,
- performing, by the analysis unit [200c] at the SNMP parser unit [200], a delta analysis for a subset of the one or more performance counters, wherein the subset of the one or more performance counters comprises a set of performance counters for which the non-existing status is determined;
- parsing, by a parser [200d] at the SNMP parser unit [200], a raw data file from the compressed raw data based on the performance of the delta analysis, to generate a parsed data file; and
- storing, in a storage unit [200e] at the SNMP parser unit [200], the parsed data file.
2. The method as claimed in claim 1, wherein the performing, by the analysis
unit [200c] at the SNMP parser unit [200], the delta analysis, based on the
determined availability of the previous file related to the compressed raw
data, further comprises:

- assigning, by the analysis unit [200c] at the SNMP parser unit [200], a
raw value as a delta value in an event of determination of the non-
existing status.
3. The method as claimed in claim 1, wherein the omit list comprises one or more of a node name, a host name, a category name, and a counter name.
4. The method as claimed in claim 1, wherein the existing status is determined in an event the performance counter is existing in the omit list, and the non-existing status is determined in an event the performance counter is not existing in the omit list.
5. The method as claimed in claim 2, wherein the performing, by the analysis unit [200c] at the SNMP parser unit [200] via a distributed computing clusters unit [202], the delta analysis, is done in parallel, by one or more distributed computing clusters in the distributed computing clusters unit [202].
6. The method as claimed in claim 1, wherein the storing, in the storage unit [200e] at the SNMP parser unit [200], the parsed data file, further comprises:
- compressing, by the parser [200d] at the SNMP parser unit [200], the
parsed data file.
7. The method as claimed in claim 1, wherein the performing, by the analysis unit [200c] at SNMP parser unit [200], the delta analysis, based on the determined availability of the previous file related to the compressed raw data is done on the file system component [204].
8. The method as claimed in claim 1 further comprising: extracting, by the extraction unit [200b] at the SNMP parser unit [200] at a desired location, the raw data file from the compressed raw data.
9. The method as claimed in claim 8, wherein in an event the absent status of the previous file related to the compressed raw data is determined by the extraction unit [200b], the method comprises: storing, in the storage unit

[200e] at the SNMP parser unit [200], the raw data file extracted from the compressed raw data.
10. The method as claimed in claim 1 wherein the available status is determined in an event the previous file related to the compressed raw data is available, and the absent status is determined in an event the previous file related to the compressed raw data is not available.
11. The method as claimed in claim 1 wherein in an event the non-existing status is determined for a target performance counter from the one or more performance counter, the method further comprises: adding, by the analysis unit [200c] at the SNMP parser unit [200], the target counter to the omit list.
12. A simple network management protocol (SNMP) parser unit [200] for performing delta analysis, the SNMP parser unit [200] further comprising:

- a transceiver unit [200a] configured to receive a compressed raw data from a file system component [204] at a pre-defined interval of time, wherein the compressed raw data comprises one or more performance counters;
- an extraction unit [200b] connected to the transceiver unit [200a], wherein the extraction unit [200b] is configured to:
o determine one of: an available status and an absent status of a previous file related to the compressed raw data;
- an analysis unit [200c] connected to the extraction unit [200b], wherein
the analysis unit [200c] is configured to:
o determine for each performance counter of the one or more performance counters, an existence status of each performance counter in an omit list in an event of determination of the available status, wherein the existence status is one of: an existing status and a non-existing status,
o perform a delta analysis for a subset of the one or more performance counters, wherein the subset of the one or more

performance counters comprises a set of performance counters for which the non-existing status is determined;
- a parser [200d] connected to the analysis unit [200c], wherein the parser [200d] is configured to parse a raw data file from the compressed raw data based on the performance of the delta analysis, to generate a parsed data file; and
- a storage unit [200e] connected to at least the parser [200d], wherein the storage unit [200e] is configured to store the parsed data file.
13. The SNMP parser unit [200] as claimed in claim 12, wherein the analysis
unit [200c] is configured to perform the delta analysis, based on the
determined availability of the previous file related to the compressed raw
data, is further configured to:
- assign a raw value as a delta value in an event of determination of the
non-existing status.
14. The SNMP parser unit [200] as claimed in claim 12, wherein the omit list comprises one or more of a node name, a host name, a category name, and a counter name.
15. The SNMP parser unit [200] as claimed in claim 12, wherein the existence status is one of an existing status and a non-existing status, and wherein the existing status is determined in an event the performance counter is existing in the omit list, and the non-existing status is determined in an event the performance counter is not existing in the omit list.
16. The SNMP parser unit [200] as claimed in claim 13, wherein the analysis unit [200c] is configured to perform via a distributed computing clusters unit [202], the delta analysis, is done in parallel, by one or more distributed computing clusters in the distributed computing clusters unit [202].
17. The SNMP parser unit [200] as claimed in claim 12, wherein the storage unit [200e] is configured to store the parsed data file, is further configured to compress, by the parser [200d], the parsed data file.

18. The SNMP parser unit [200] as claimed in claim 12, wherein the analysis unit [200c] is configured to perform the delta analysis, based on the determined availability of the previous file related to the compressed raw data, on the file system component [204].
19. The SNMP parser unit as claimed in claim 12 wherein the extraction unit [200b] is further configured to extract, at a desired location, the raw data file from the compressed raw data.
20. The SNMP parser unit as claimed in claim 19, wherein in an event the absent status of the previous file related to the compressed raw data is determined by the extraction unit [200b], the storage unit [200e] is configured to store the raw data file extracted from the compressed raw data.
21. The SNMP parser unit as claimed in claim 12, wherein the available status is determined in an event the previous file related to the compressed raw data is available, and the absent status is determined in an event the previous file related to the compressed raw data is not available.
22. The system as claimed in claim 12, wherein in an event the non-existing status is determined for a target performance counter from the one or more performance counter, the analysis unit [200c] is further configured to add the target counter to the omit list.
23. A user equipment (UE) for performing delta analysis by a simple network management protocol (SNMP) parser unit [200], the UE comprising:

- a memory; and
- a processor coupled to the memory, wherein the processor is configured to:
o transmit to the SNMP parser unit [200], a compressed raw data from a file system component [204] at a pre-defined interval of time, wherein the compressed raw data comprises one or more performance counters, and
o receive from the SNMP parser unit [200], a response comprising a parsed data file,
wherein the response is received based on:

determining, at the SNMP parser unit [200], one of: an available status and an absent status of a previous file related to the compressed raw data,
determining, at the SNMP parser unit [200], for each performance counter of the one or more performance counters, an existence status of each performance counter in an omit list in an event of determination of the available status, wherein the existence status is one of: an existing status and a non-existing status,
performing, at the SNMP parser unit [200], a delta analysis for a subset of the one or more performance counters, wherein the subset of the one or more performance counters comprises a set of performance counters for which the non-existing status is determined,
parsing, at the SNMP parser unit [200], a raw data file from the compressed raw data based on the performance of the delta analysis, to generate the parsed data file, and
storing, at the SNMP parser unit [200], the parsed data file.